Systems and methods for lossless compression of data and high speed manipulation thereof

ABSTRACT

The present disclosure includes a system, method, and article of manufacture for lossless compression of data and high speed manipulation of the data. The method may comprise associating a customer with a plurality of levels, and counting, in near real time, a number of transactions at each level in the plurality of levels based on a transaction history of the customer at each of a plurality of merchants. The method may further comprise counting the number of transactions during a time period. Similarly, the method may comprise determining an opportunity comprising an offer based upon the counting, determining an opportunity based upon a count indicating a transaction by the customer with a merchant, and/or determining an opportunity with a first merchant based upon a count indicating a transaction by the customer with a second merchant.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. application Ser. No.13/591,013, filed Aug. 21, 2012 (now U.S. Pat. No. 8,914,545), which isa continuation in part of U.S. application Ser. No. 13/095,679, filedApr. 27, 2011 (now U.S. Pat. No. 8,412,849); the disclosures of each ofthe above-referenced applications are incorporated by reference hereinin their entireties.

BACKGROUND

Field

The present disclosure generally relates to compression of data, andmore particularly, to lossless compression of data and high speedmanipulation thereof.

Related Art

There are many instances in which it is advantageous to inquire into theactivity and/or attributes associated with a particular individual(e.g., a computer user, a transaction account holder, a consumer, andthe like). For example, many organizations sometimes go to great expenseto remain apprised of the network activities of their employees. Thatis, a large number of organizations often expend a large amount of moneyand time determining which websites/domains their employees surf (anactivity), which network permissions their employees may be assigned (anattribute), and the like. Similarly, many organizations (e.g., salesorganizations, transaction account issuers or payment processors, andthe like) may utilize information associated with, for example, thebrowsing activities and/or transaction histories of their customers tobetter tailor content (e.g., offers, opportunities, rewards, and thelike) to those customers.

In the past, the size and complexity of such data has limited the speedand efficiency with which this data may be analyzed or processed. Forexample, where an organization wishes to track a website that anemployee visits and/or a database of each permission assigned to eachemployee, the processing and memory requirements may escalate rapidly,particularly where there are a large number of employees surfing to alarge number of websites, or a large number of employees associated witha particular permission or group of permissions (only some of which maybe necessary for the performance of the employee's assignments).Similarly, where a transaction account issuer or payment processorwishes to analyze, for example, transaction history data associated withits customers, often the complexity and quantity of this data may againgive rise to rapidly escalating processing and memory requirements.

Accordingly, systems and methods capable of rapidly and inexpensivelycompressing and manipulating large amounts of data (e.g., datacomprising an employee's activity or attributes on or within a network,transaction history, and the like) are desirable and would be of greatadvantage to a large number of organizations and businesses. Inparticular, solutions that reduce memory and processing requirements maybe very advantageous.

SUMMARY

The present disclosure includes a system, method, and article ofmanufacture for lossless compression of data and high speed manipulationof data. The method may comprise associating a customer with a pluralityof levels and/or merchants, where a number of transactions associatedwith one or more spend levels (e.g., high, medium, low) at each merchantmay be counted (in near real time) for the customer. In variousembodiments, the method may further comprise counting the number oftransactions during a time period. Similarly, the method may comprisedetermining an opportunity comprising an offer based upon the counting,determining an opportunity based upon a count indicating a transactionby the customer with a merchant, determining an opportunity with a firstmerchant based upon a count indicating a transaction by the customerwith a second merchant, determining a loyalty opportunity with amerchant based upon a count indicating a transaction by the customerwith the merchant during a time period, and/or determining anopportunity with a merchant based upon a count and an indication by thecustomer that the customer is visiting the merchant.

BRIEF DESCRIPTION OF THE DRAWINGS

The features and advantages of the present disclosure will become moreapparent from the detailed description set forth below when taken inconjunction with the drawings. The left-most digit of a reference numberidentifies the drawing in which the reference number first appears.

FIG. 1 shows an exemplary system diagram in Which an individual mayinteract or interface with an organization, in accordance with variousembodiments.

FIG. 2 shows a flowchart depicting an exemplary process for associatingentities and collections with binary numbers, in accordance with variousembodiments.

FIG. 3 shows an exemplary entity cross-reference table, in accordancewith various embodiments.

FIG. 4 shows an exemplary collections table, with the binaryrepresentation showing the entities included in each collection, inaccordance with various embodiments.

FIG. 5 shows an exemplary monthly summary table for some period of time,e.g., days of the month, and the associated entities for eachcollection, in accordance with various embodiments.

FIG. 6 shows an exemplary summary collections table including used andassigned entity data, in accordance with various embodiments.

FIG. 7 shows a flowchart depicting an exemplary process for associatingan entity with level data, in accordance with various embodiments.

FIG. 8A shows an exemplary level cross-reference table, in accordancewith various embodiments.

FIG. 8B shows an exemplary level cross-reference table, in accordancewith various embodiments.

FIG. 9 shows an exemplary level data collections table, in accordancewith various embodiments.

FIG. 10 shows an exemplary monthly level data collections table for someperiod of time, e.g., days of the month, in accordance with variousembodiments.

FIG. 11 shows an exemplary summary level data collections table with themaximum values that occurred during the given period of time, inaccordance with various embodiments.

FIG. 12 shows an exemplary risk level cross-reference table, inaccordance with various embodiments.

FIG. 13 shows an exemplary risk level data collections table, inaccordance with various embodiments.

FIG. 14 shows an exemplary risk level transaction count table, where then^(th) array element holds the associated count for the n^(th) entity inthe binary representation of the entities in the collection, inaccordance with various embodiments.

FIG. 15 shows an exemplary diagram in which a transaction is processedand/or analyzed, in accordance with various embodiments.

FIG. 16 shows an exemplary table with daily customer spend eventsorganized by merchant and purchase level, in accordance with variousembodiments.

FIG. 17 shows an exemplary table with monthly customer spend eventcounts organized by merchant and purchase level, in accordance withvarious embodiments.

DETAILED DESCRIPTION

The detailed description of exemplary embodiments herein makes referenceto the accompanying drawings, which show the exemplary embodiments byway of illustration and their best mode. While these exemplaryembodiments are described in sufficient detail to enable those skilledin the art to practice the disclosure, it should be understood thatother embodiments may be realized and that logical and mechanicalchanges may be made without departing from the spirit and scope of thedisclosure. Thus, the detailed description herein is presented forpurposes of illustration only and not of limitation. For example, thesteps recited in any of the method or process descriptions may beexecuted in any order and are not limited to the order presented.Moreover, any of the functions or steps may be outsourced to orperformed by one or more third parties. Furthermore, any reference tosingular includes plural embodiments, and any reference to more than onecomponent may include a singular embodiment.

The phrases consumer, customer, user, account holder, cardmember or thelike shall include any person, entity, business, governmentorganization, business, software, hardware, machine associated with atransaction account, buys merchant offerings offered by one or moremerchants using the account and/or who is legally designated forperforming transactions on the account, regardless of whether a physicalcard is associated with the account. For example, the cardmember mayinclude a transaction account owner, an transaction account user, anaccount affiliate, a child account user, a subsidiary account user, abeneficiary of an account, a custodian of an account, and/or any otherperson or entity affiliated or associated with a transaction account. Inaddition, as used herein, a user may comprise, in various embodiments,any person who interacts and/or interfaces with a computer system (e.g.,an organizational and/or an employer computer system).

As used herein, the phrases “real time,” “near real time,” “pseudo realtime,” “quasi real time,” and the like may mean any period of timeduring which a table or data structure, as described herein, is analyzedor processed. For example, in various embodiments, any of these termsmay mean a period of time immediately following and/or shortly followinga transaction, an event, an occurrence, and the like. In variousembodiments, the period of time may include a period of picoseconds,nanoseconds, microseconds, milliseconds, seconds, minutes, hours, days,and the like.

Phrases and terms similar to “transaction account” may include anyaccount that may be used to facilitate a financial transaction.

Phrases and terms similar to “financial institution” or “transactionaccount issuer” may include any entity that offers transaction accountservices. Although often referred to as a “financial institution,” thefinancial institution may represent any type of bank, lender or othertype of account issuing institution, such as credit card companies, cardsponsoring companies, or third party issuers under contract withfinancial institutions. It is further noted that other participants maybe involved in some phases of the transaction, such as an intermediarysettlement institution.

Phrases and terms similar to “business” or “merchant” may be usedinterchangeably with each other and shall mean any person, entity,distributor system, software and/or hardware that is a provider, brokerand/or any other entity in the distribution chain of goods or services.For example, a merchant may be a grocery store, a retail store, a travelagency, a service provider, an on-line merchant or the like.

A system, method and/or computer program product for losslesscompression of data is disclosed. The data may be manipulated in acompressed state very efficiently and at high speed. Referring broadlyto FIGS. 1 and 15, exemplary systems 100 and 1500 for losslesscompression and high-speed efficient manipulation of data are disclosed.Further, in various embodiments, system 100 may represent or illustratea system through which an employer or organization and an employee orindividual interact, while in various embodiments, system 1500 mayrepresent or illustrate a system for processing and/or analyzing atransaction history (e.g., a history of payment transactions and/or anactivity history of a user and/or system).

With particular reference to FIG. 1, system 100 may comprise a webclient 102, a network 104, and/or a database 106. In an exemplaryembodiment, system 100 may comprise a mainframe system and/or a singledistributed system.

A web client 102 includes any device (e.g., personal computer, point ofsale or POS device) which communicates via any network, for example suchas those discussed herein. Such browser applications comprise Internetbrowsing software installed within a computing unit or a system toconduct online transactions and/or communications. These computing unitsor systems may take the form of a computer or set of computers, althoughother types of computing units or systems may be used, includinglaptops, notebooks, tablets, hand held computers, mobile phones, smartphones, personal digital assistants, set-top boxes, workstations,computer-servers, main frame computers, mini-computers, PC servers,pervasive computers, network sets of computers, personal computers, suchas IPADS, iMACs, and MacBooks, kiosks, terminals, point of sale (POS)devices and/or terminals, televisions, or any other device capable ofreceiving data over a network. A web-client 102 may run MicrosoftInternet Explorer, Mozilla Firefox, Google Chrome, Apple Safari, or anyother of the myriad software packages available for browsing theinternet.

Practitioners will appreciate that a web client 102 may or may not be indirect contact with an application server. For example, a web client 102may access the services of an application server through another serverand/or hardware component, which may have a direct or indirectconnection to an Internet server. For example, a web client 102 maycommunicate with an application server via a load balancer. In anexemplary embodiment, access is through a network or the Internetthrough a commercially-available web-browser software package.

As those skilled in the art will appreciate, a web client 102 includesan operating system (e.g., Windows NT, 95/98/2000/CE/Mobile, OS2, UNIX,Linux, Solaris, MacOS, PalmOS, etc.) as well as various conventionalsupport software and drivers typically associated with computers. A webclient 102 may include any suitable personal computer, network computer,workstation, personal digital assistant, cellular phone, smart phone,minicomputer, mainframe or the like. A web client 102 can be anywherethere is any type of wireless network connectivity (e.g., in a home orbusiness environment with access to a network). In an exemplaryembodiment, access is through a network or the Internet through acommercially available web-browser software package. A web client 102may implement security protocols such as Secure Sockets Layer (SSL) andTransport Layer Security (TLS). A web client 102 may implement severalapplication layer protocols including http, https, ftp, and sftp.

In various embodiments, components, modules, and/or engines of system100 may be implemented as micro-applications or micro-apps. Micro-appsare typically deployed in the context of a mobile operating system,including for example, a Palm mobile operating system, a Windows mobileoperating system, an Android Operating System, Apple iOS, a Blackberryoperating system and the like. The micro-app may be configured toleverage the resources of the larger operating system and associatedhardware via a set of predetermined rules which govern the operations ofvarious operating systems and hardware resources. For example, where amicro-app desires to communicate with a device or network other than themobile device or mobile operating system, the micro-app may leverage thecommunication protocol of the operating system and associated devicehardware under the predetermined rules of the mobile operating system.Moreover, where the micro-app desires an input from a user, themicro-app may be configured to request a response from the operatingsystem which monitors various hardware components and then communicatesa detected input from the hardware to the micro-app. In variousembodiments, a micro-app may be made available as a service.

As used herein, network 104 includes any cloud, cloud computing systemor electronic communications system or method which incorporateshardware and/or software components. Communication among the parties maybe accomplished through any suitable communication channels, such as,for example, a telephone network, an extranet, an intranet, Internet,point of interaction device (point of sale device, personal digitalassistant (e.g., IPHONE, PALM PILOT, BLACKBERRY), cellular phone, kiosk,etc.), online communications, satellite communications, off-linecommunications, wireless communications, transponder communications,local area network (LAN), wide area network (WAN), virtual privatenetwork (VPN), networked or linked devices, keyboard, mouse and/or anysuitable communication or data input modality. Moreover, although thesystem is frequently described herein as being implemented with TCP/IPcommunications protocols, the system may also be implemented using IPX,Appletalk, IP-6, NetBIOS, OSI, any tunneling protocol (e.g. IPsec, SSH),or any number of existing or future protocols. If the network is in thenature of a public network, such as the Internet, it may be advantageousto presume the network to be insecure and open to eavesdroppers.Specific information related to the protocols, standards, andapplication software utilized in connection with the Internet isgenerally known to those skilled in the art and, as such, need not bedetailed herein. See, for example, Dilip Naik, Internet Standards andProtocols (1998); Java 2 Complete, various authors, (Sybex 1999);Deborah Ray and Eric Ray, Mastering HTML 4.0 (1997); and Loshin, TCP/IPClearly Explained (1997) and David Gourley and Brian Totty, HTTP, TheDefinitive Guide (2002), the contents of which are hereby incorporatedby reference.

The various system components may be independently, separately orcollectively suitably coupled to the network via data links whichincludes, for example, a connection to an Internet Service Provider(ISP) over the local loop as is typically used in connection withstandard modem communication, cable modem, Dish networks, ISDN, DigitalSubscriber Line (DSL), or various wireless communication methods, see,e.g., Gilbert Held, Understanding Data Communications (1996), Which ishereby incorporated by reference. It is noted that the network may beimplemented as other types of networks, such as an interactivetelevision (ITV) network. Moreover, the system contemplates the use,sale or distribution of any goods, services or information over anynetwork having similar functionality described herein.

“Cloud” or “Cloud computing” includes a model for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, servers, storage, applications, and services)that can be rapidly provisioned and released with minimal managementeffort or service provider interaction. Cloud computing may includelocation-independent computing, whereby shared servers provideresources, software, and data to computers and other devices on demand.For more information regarding cloud computing, see the NIST's (Nationalinstitute of Standards and Technology) definition of cloud computing athttp://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf (lastvisited June 2012), which is hereby incorporated by reference in itsentirety.

Database 106 may comprise any type of hardware and/or software (e.g., acomputer server) configured or configurable to store data and/or host adatabase. For example, database 106 may comprise a server appliancerunning a suitable server operating system (e.g., IIS) and havingdatabase software (e.g., SQL Server 2008, an Oracle database, and thelike), stored thereon, Database 106 may, in various embodiments,compress and/or analyze data, as described herein. Similarly, in variousembodiments, database 106 may be coupled to a system for analyzingand/or compressing data, as described herein.

With particular reference to FIG. 15, system 1500 may comprise a client1502, a network 1504, a global authorization network (“GAN”) 1506,and/or an analytics system 1508.

In various embodiments, web client 1502 may comprise a client similar oridentical to web client 102, as described above. For example, in variousembodiments, client 1502 may comprise a personal computer, a mobilecomputer, a mobile phone, a POS device, and the like.

Similarly, in various embodiments, network 1504 may comprise a networksimilar or identical to network 104, as described above. Further, invarious embodiments, network 1504 may comprise an inbound acquiringnetwork associated with a financial institution or other transactionaccount issuer or manager.

In various embodiments, GAN 1506 may comprise a system (e.g., a frontend or initial authorization system) capable of or configured to performall or part of an authorization process in relation to a paymenttransaction associated with a transaction account.

In various embodiments, analytics system 1508 may comprise a system(e.g., a back end or secondary authorization system) capable of orconfigured to perform all or part of an authorization process inrelation to a payment transaction associated with a transaction account.For example, analytics system 1508 may comprise a card authorizationsystem (“CAS”).

Referring broadly now to FIGS. 2-14 and 16-17, the process flows,logical representations, and/or screen shots depicted are merelyembodiments and are not intended to limit the scope of the disclosure.For example, the steps recited in any of the method or processdescriptions may be executed in any order and may, in variousembodiments, apply to the systems 100 and/or 1500 depicted,respectively, in FIGS. 1 and 15. It will be appreciated that thefollowing description makes appropriate references not only to the stepsdepicted in FIGS. 2-14 and 16-17 but also to the various systemcomponents and/or logical representations as described above withreference to FIGS. 1 and 15.

With reference now to FIG. 2, an exemplary process 200 for losslesscompression and efficient manipulation of data is disclosed. As aprimer, the following definitions apply.

Broadly, a “collection” may comprise a group or cluster of “entities,”and an “entity” may comprise any element, part, or aspect of acollection. To clarify, although the foregoing definitions are not solimited, an entity may comprise any transaction, activity, occurrence,event, system, user, customer, consumer, merchant, attributes, and thelike that may be associated with a collection, and a collection maycomprise any group or cluster of transactions, activities, occurrences,events, systems, users, merchants, customers, consumers, attributes, andthe like. Moreover, a collection may in one instance operate as anentity, and an entity, likewise, as a collection.

Take, for example, a collection comprising a user (a “user collection”).A variety of entities may be associated with the user collection; but,to take a single entity for purposes of illustration, a variety oftransaction entities (e.g., visits to a website/domain or file accessattempts) may be associated with the user collection. Thus, the user maycomprise a collection of transaction entities. More particularly, inthis case, the user collection may comprise one or more visits by theuser to a website/domain or accesses by the user of a file.

However, and as mentioned above, a collection may in one instanceoperate as an entity, and the entity a collection. For example, atransaction entity (e.g., a website or a file) may operate as acollection, while a user may operate as an entity that accesses thewebsite/file collection. Thus, in this example, the website or file maycomprise a collection of user entities which have accessed the websiteor file collection.

Thus, the terms “entity” and “collection” may be, at the most basiclevel, defined by their relationship to one another. In other words,because a user may comprise a collection in one scenario, but an entityin another scenario, it is helpful to realize that the terms are bestunderstood as a one-to-one, one-to-many, or many-to-many relationshipbetween two interrelated data sets or elements.

Accordingly, and for purposes of illustration, several examples ofcollection-entity relationships are provided. In various embodiments, anentity may comprise one or more transactions, users, user activities,internet sites, internet proxy activities, systems, alerts from systemsor processes, anti-virus activities, data leakage prevention events,system activities, and the like. Likewise, a collection may comprise, invarious embodiments, any of the foregoing, including one or more users,user groups, transaction clusters, activities associated with one ormore users, files, file permissions, system alerts, websites/domains,and the like.

Similarly, in various embodiments, a collection may comprise anindividual or customer (e.g., a customer of a transaction accountissuer), while an entity may comprise one or more merchants from whomthe customer collection has made purchases. However, as described above,the collection-entity relationship between merchants and customers maybe defined such that a merchant comprises a collection, while customerscomprise entities.

With continuing reference to FIG. 2, an entity may be associated with aunique power of the number two (step 202). For example, six entities,labeled A, B, C, D, E, and F, may be associated with unique powers oftwo using the number two as the base and (n−1) as the exponent, or2^((n-1)), where n=1 to 6, in this example, but where n generally beginswith the number one and increases until each entity is associated with aunique value. The value associated with each entity may be furtherconverted to binary (step 204). Thus, where there are six entities, Athrough F, each entity may receive base 10 and binary values as follows:

-   -   A: 2⁽⁰⁾=1=000001    -   B: 2⁽¹⁾=2=000010    -   C: 2⁽²⁾=4=000100    -   D: 2⁽³⁾=8=001000    -   E: 2⁽⁴⁾=16=010000    -   F: 2⁽⁵⁾=32=100000

Although a variety of mechanisms may be employed, in an embodiment, therelationships between each entity and its base 10 and/or binary valuemay be saved in a table or array, which may comprise a portion of adatabase (other mechanisms may include that files, objects in an objectoriented program, and the like). For example, database 106 may storethese relationships as part of an entity cross-reference table, which isdepicted in FIG. 3.

As stated, a collection may comprise a cluster, collection, and/or groupof one or more entities. Thus, where there are, for example, fivecollections, C1, C2, C3, C4, and C5, each collection may includeentities as follows:

-   -   C1: A, B, C,    -   C2: A, B, C    -   C3: A, B, E    -   C4: F    -   C5: A, B,

Like each entity, each collection C1-C5 may be associated with a base 10and/or binary value. This may be accomplished by summing the base 10values of each unique entity in a collection and converting those valuesto binary. In an embodiment, the binary values associated with eachunique entity in a collection may be logically ORed to produce the sameresult (step 206). In the example above, the following results areobtained:

-   -   C1: A+B+C+D=1+2+4+8=15=001111    -   C2: A+B+C=1+2+4=7=000111    -   C3: A+B+E=1+2+16=19=010011    -   C4: F=32=100000    -   C5: A+B+C=1+2+4=7=000111

As described above with reference to each entity value, each collectionvalue may be stored in a database (e.g., database 106) as part of acollections table, which is depicted in FIG. 4.

At this point, in one embodiment, 512 unique entities (to pick a numbersolely for purposes of illustration) may be mapped uniquely using 512bits, or 64 bytes. Assuming a period of 30 days at a rate of 500entities per day per collection (e.g., a user collection performing upto 500 distinct transactions per day) and 20,000 collections (e.g.,20,000 users), only about 38 megabytes of storage are required to storeall of the data generated for the entire month. Thus, the data iscompressed, in that a fraction of the storage previously required totrack a collection's entities is required by the systems and methodsdescribed herein. Moreover, the data is stored losslessly, because allof the information associated with a collection's entities is storedintact as set of binary values.

The unique numbering system described above gives rise to a variety ofunique and useful results (step 208). For instance, if a collection hasa same entity sum as another collection, those collections areidentical. That is, observe that collections C2 and C5, which bothcomprise entities A, B, and C, are associated with a base 10 sum of 7,or a binary sum of 000111. Thus, a simple numerical comparison showsduplicate collections. Further, because computing devices are designedto process data in a binary format (as opposed to a character orcharacter string format, or even a base 10 format), the comparisondescribed above may be performed at very high speed. That is, nocomputationally intensive string matching is required with the disclosedsystem.

Observe further that any collection that is associated with a value of2^((n-1)) necessarily includes only a single entity (e.g., a collectionassociated with a value of 1, 2, 4, 8 . . . only includes the entityassociated with that value). On the other hand, any collection that isnot associated with a value of 2^((n-1)) is not limited to a singleentity, and may include entities in common with other collections. Forexample, with reference to collections C1 and C3, system 100 may use alogical AND operation to quickly determine that these collections shareentities in common and, indeed, which entities are shared. Thecalculation is provided below:00111 (C1) AND 010011 (C3)=000011 (Result)

Having reached this Result, system 100 may use the entitycross-reference table (depicted in FIG. 3) to determine that the Resultcontains entities A and B (as stated, A=000001 and B=000010). Thus,system 100 may quickly determine which entities a plurality ofcollections share in common. In addition, system 100 may associate anentity count with a plurality of collections, whereby system 100 maydetermine collections that are candidates for entityreduction/consolidation and/or likely include entities included in othercollections. That is, collections with a high entity count may be morelikely to share common entities.

From a practical standpoint, although many uses are possible, assumethat a first and second collection comprise two different network usergroups (e.g., group C1 and group C2). Assume further that these groupscomprise a variety of network users (e.g., users A, B, and C). Moreparticularly, assume:

-   -   Group C1: user A, user B, user C    -   Group C2: user A, user B

System 100 may determine, based upon the processes described above, thatGroups C1 and C2 both include users A and B. A system or networkadministrator may use this information to collapse, remove, and/ordelete group C2, particularly where the administrator is able to placeuser C in a different group (not shown). Thus, the disclosed system andmethod may, in an example, permit a system or network administrator toremove redundant or unnecessary user groups.

With further regard to the manner in which entities may be assigned avalue, the speed at which system 100 operates may be further improved bycalculating, prior to assigning each entity in a collection a value, therelative frequencies of each entity across a plurality of collections.Those entities that occur most commonly may be assigned lower values(e.g., 1 or 000001), while those entities that occur less commonly maybe assigned higher values (e.g., 32 or 100000). In this way, long binaryrepresentations can be partitioned into subsets that enable fasterlogical operations. For example, using the 512 entity example above,frequent entities are placed in the low order bytes (i.e., to the right,as shown in the example). Searching (or updating) the collections for agiven common entity can be completed by performing the logical AND(respectively OR) on only the right most bytes and not the full 64 byteblocks. In an embodiment, the binary encoding can be completed so thatsimilar or related entities are “close” together in the binaryrepresentation. This too enables partitioning the binary representationfor efficient searching and/or updates of similar or related entities.With reference to FIG. 4, further efficiencies may be achieved byincluding a field for the number of entities in the collection orseveral fields for the number of entities in each of the partitionedsubsets.

The foregoing processes, tables, and/or computations may be enhanced ina variety of ways. For instance, a collection table may be enhanced toshow periodic (e.g., hourly, daily, weekly, monthly, 90 day, annual,etc.) entity sums, in which case a collection may be evaluated moregranularly. This is depicted at FIG. 5. With respect to FIG. 5, notethat Day_M is merely intended to represent the final day in a period ofdays. So, if the period is one month, M may equal 28, 29, 30, or 31,depending upon the month and year. Moreover, where a period is verygranular (e.g., hourly) a trending analysis may be performed by system100 to show a real time (or almost or pseudo-real time/quasi-real time)behavior of one or more collections and/or entities.

In an embodiment, a collection table may include entries for entities“used” by a collection and entries for entities “assigned” to acollection. This enhancement may be helpful, in one example, to systemadministrators in determining whether a user collection is using all,fewer, or greater than the permissions entities that it (or be) isassigned. Table 6 shows this enhancement, and “used” and “assigned” maybe merely illustrative and are not exclusive of other similar columns,such as “detected,” for an alert or event, and “base events,” where acollection comprises a group, such as a business unit within anorganization.

Occasionally, it may be desirable to add granularity to the data storedfor an entity. That is, it may be useful to know/determine more thanwhether an entity occurred or exists. For example, where an entitycomprises a file, the method described above may enable determination ofwhether the file was accessed. Likewise, where an entity comprises amerchant (as described herein), the systems and methods described hereinmay enable determination of whether a customer made a purchase from themerchant. However, if it is important to know, for example, a type offile access (e.g., none, read, write, alter, control, update, etc.), atype or category of transaction that occurred with a particularmerchant, and the like, additional tables and/or a different tablestructure may be helpful and/or useful. Hereinafter, such data may betracked using “level” data, or simply “levels,” depending upon thecontext in which the terms appear. As described herein, and for purposesof illustration, level data may include a type of file access (e.g.,read, write, etc.), a type of transaction (e.g., a transaction of afirst value, a transaction of a second value, a transaction with amerchant in a particular industry group, and the like). In certainembodiments, any number of levels may be associated with an entity,depending upon the nature of the entity (e.g., user entity, file entity,etc.) and the granularity and information desired.

With reference now to FIG. 7, a process 700 for associating level datawith an entity is described. The process is similar to the processdescribed above, with reference to FIG. 2. Specifically, each desiredlevel must be associated with a unique value (step 702). The uniquevalue may comprise a base 10 number, a binary number, a character orcharacter string, and/or any combination thereof (Note that in caseswith large numbers of levels one may want to avoid using character orcharacter strings for performance reasons.) For example, where an entitycomprises a file or file access attempt (and the collection is a user),the file or file access attempt may be associated with a level dependingupon the result of the access attempt. In this example, potential levelsinclude none, read, update (e.g., writer or alter), control, and/orexecute. The levels can be used to distinguish between granted andconsumed access, e.g., read attempted and read granted, read attemptedand read denied, write attempted and write granted, write granted andwrite denied, and the like. Potential unique values for each levelinclude, N (none), R (read), W (write), U (update), A (alter), 0 (non),1 (read), 2 (write), 3 (update), 4 (alter). In an embodiment, encodingcan be completed to capture attempted and granted access, such as RR or11 or 1 (read attempted and read granted), RN or 10 or 0 (read attemptedand none granted), WW or 22, or 2 (write attempted and write granted),WN or 20 or 3 (write attempted and none granted), etc. In certainembodiments, any value, string, and/or combination thereof may beassigned to a level or the combination of attempted versus granted, etc.The only requirement is that each level be assigned a unique identifier.As described above with reference to the entity cross-reference table(see FIG. 3), so too, the level data associated with each entity may bestored in a level cross-reference table. Exemplary level cross-referencetables are depicted at FIGS. 8A and 8B.

With further reference to FIG. 7, in order to capture level dataassociated with an entity (e.g., in order to capture the results of afile access attempt), each entity in a collection may be associated withan appropriate level, based upon the data contained in the levelcross-reference table (step 704). This may be achieved by creating atable or array of level data, where the n^(th) array element for thelevel is associated with the n^(th) bit position for the entity in thebinary representation for the entities in the associated collection.Likewise, in various embodiments, level data may be represented as aninteger (e.g., a big integer) or string, where, for example, the n^(th)bit position corresponds to the n^(th) entity. The following example,which uses entities A, C, and D, as above with reference to FIG. 2, isillustrative.

Entities:

-   -   A: 000001    -   C: 000100    -   D: 001000

Collection 1:

-   -   A, C, D: 001101

Level Data for Entities A, C, and D:

-   -   A: 2    -   C: 5    -   D: 3

Level Data Array for Collection 11:

-   -   0∥0∥3∥5∥0∥2

Thus, the level data for each entity A, C, and D in Collection 1 isstored in a level data array, where the array position corresponds tothe bit position of the entity in Collection 1 with which it isassociated. In certain embodiments, vertical bars may be used herein toseparate level data elements in a level data array to depict the arraynature of a level data array. However, in practice, a level data arraymay not include vertical bars. One or more level data arrays may bestored in a level data collections table, an example of which isdepicted at FIG. 9. Each level data array comprising a level datacollections table may, in conjunction with a level data cross-referencetable, permit a variety of more advanced analyses (step 706). Forexample, where a collection, C1, comprises a file, and the entitiesassigned to C1 comprise users A, B, and C attempting to access the file,system 100 may use the process described with reference to FIG. 2 todetermine that users A, B, and C accessed (or attempted to access) thefile collection, and the process described with reference to FIG. 7 todetermine specific details about the access attempts by users A, B, andC (e.g. read attempted, read granted, etc.) Thus, for example, system100 may identify potential excessive granted access that is not beingused during a given time period, possible accidental or maliciousattempted access, and the like.

A level data collections table may be enhanced in a variety of ways. Forinstance, a level data collection table may be enhanced to show periodic(e.g., hourly, daily, weekly, monthly, 90 day, annual, etc.) level datafor the associated collection, which enables evaluation with moregranularity. An enhanced monthly level data collections table isdepicted at FIG. 10. With reference to FIG. 10, note that Day_M ismerely intended to represent the final day in a period of days. So, ifthe period is one month, M may equal 28, 29, 30, or 31, depending uponthe month and/or year. Moreover, where a period is very granular (e.g.,hourly) a trending analysis may be performed by system 100 to show areal time (or almost or pseudo-real time or quasi-real time) behavior ofone or more collections and/or entities. Further still, a Boolean flagmay indicate whether an entity has been active (e.g., existed and/oroccurred) during an interval (e.g., the last 30, 60, 90, etc. days).

A level data collections table may be further enhanced to provide aminimum or maximum array level for each associated entity for a givencollection during a given period. For example, a level data collectionstable may include a maximum level associated with one each entity in ormore collections during a given month. An exemplary summary level datacollections table including this data is depicted at FIG. 11, Again, aBoolean flag may indicate whether an entity has been active (e.g.,existed and/or occurred) during an interval (e.g., the last 30, 60, 90,etc. days).

In addition to providing details about an entity, level data may beleveraged to assess the risk associated with a particular entity. Forexample, where an entity comprises a file, and the collection associatedwith the entity comprises a user, level data may be leveraged todetermine the risk associated with the user's file access attempts. Thatis, where a user attempts to access a file and access is denied (becausethe user does not have permission to access the file), a higher risk maybe associated with the user or the user's activities. This risk may beassociated with a risk level, which may be defined in any suitablemanner. For example, a risk may be assigned a risk level of 1 to 10, 0to 9, low, medium, high, etc., depending upon a variety of factors(e.g., likelihood of harm, impact of harm, etc.) This data may be storedin a risk level cross-reference table. An exemplary risk levelcross-reference table is depicted at FIG. 12. Further, a risk level maybe stored and associated with an entity and/or a collection in themanner described above with reference to level data. That is, eachentity in a collection may be associated with a risk level by storing arisk level in a risk level collections table in the array positioncorresponding to the bit position of the entity in the collection withwhich it is associated. An exemplary risk level collections table isdepicted at FIG. 13.

Further still, one or more fields, columns, arrays, and/or tables may beimplemented to capture the number of transactions associated with eachrisk level (e.g., on an entity, collection, and/or system wide level),and this data may, for instance and in the example provided above, formthe basis for a report highlighting excess user access or attemptedaccess violations, either of which may be accidental or malicious. Forexample, and with reference to FIG. 14, which depicts an exemplarymonthly risk level transaction count table, the n^(th) array element mayhold a count for the number of times that the n^(th) associated entityin the collection (e.g., activity, transaction type and/or resource) hasbeen attempted to be performed, occurred, and/or accessed. Duringmultiple events for accessing or attempting to access a resource,transaction, system, etc., the level array may simply capture themaximum access attempted. This may ensure that the worst case (i.e., themaximum level) is identified. For example, if a user is granted ALTERaccesses to a particular file and then accesses it 99 times with READaccess and once with WRITE or ALTER access then the level entry in theassociated array may show ALTER ATTEMPTED and ALTER GRANTED, e.g., 22,while the associated count in the risk level transaction count table(FIG. 14) would be 100. Additionally, the array elements may be brokendown into separate bit maps, where there may be an indicator for thevarious levels and the associated counts. For example, a 64 bit arrayelement may be used to allocate bits for different levels, with eitherassumed (based on position) or explicit level identifiers. Counts thatexceed the maximum value may simply be left at their maximum value andnot rolled to restart counting from zero. Alternatively, countsexceeding the maximum may be restarted (e.g., from zero), and a separatecounter incremented each time the maximum is achieved.

With reference now to FIG. 16, a table or array 1602 is depicted whichmay, in various embodiments, be useful for capturing or collectinginformation associated with a level, an entity, a collection, and/or atime period in a single table or array. In other words, table 1602 maypermit storage of both level data and event counts in a single datastructure. Moreover, although table 1602 is described below withreference to collection and analysis of transaction history data (e.g.,spending or purchasing history data), table 1602 may apply equally toany instance in which it is desirable to organize data according toentity, collection, level, and/or time period. For example, as describedabove, table 1602 may include level data associated with a number offile access attempts and/or types of file access attempts. In addition,although table 1602 is described as being useful for the storage andanalysis of information associated with each of an entity, a collection,a level, and/or a time period, those of skill will appreciate that thesystems and methods described above with reference to FIGS. 1-14 arealso capable of capturing the same data. Similarly, in variousembodiments, a one dimensional array may be formed that represents oneor more entities. Such an array may comprise one or more multi-bitelements (e.g., bytes), where each element is tied to an entity andwhere the bits comprising each multi-bit element are associated withlevel data for the entity.

Thus, although those of skill in the art will recognize as describedbriefly above) that other structures capable of performing the same or asimilar function may be constructed based upon this disclosure, invarious embodiments, table 1602 may be organized such that a group ofrows may comprise a single collection (e.g., customers, such as Cust1,Cust2, and Cust3, as shown, users, and the like), while each column maycomprise an entity (e.g., merchants, such as M1 . . . Mx, as shown,categories of merchants or industry groups of merchants, and the like).Further, as described below, in certain embodiments, a count or levelcount may be associated each entity. A count or level count may bestored as a two dimensional array (e.g., as bytes and/or smallintegers). Thus, a first dimension of a two dimensional array forstoring level counts may correspond to each of a plurality of entities(e.g., 1 . . . Mx), while a second dimension of the two dimensionalarray may correspond to one or more levels (e.g., L, M, H, as describedbelow). Thus, each element in a two dimensional array may store a levelcount for an entity with respect to a particular level (e.g., for then^(th) entity at the m^(th) level).

Further, in various embodiments, a group of columns or entities may begrouped into a particular time period (e.g., minutes, hours, days,weeks, months, etc.), and a group of rows comprising a collection maycomprise level data. As discussed briefly above, level data maycomprise, for example, a transaction amount or value, such as low,medium, or high (or L, M, H, as shown), a number of transactions orpurchases performed by a customer collection with a merchant entity, amerchant type (e.g., discount merchant, food retail merchant, jewelrymerchant, etc.), a type of file access attempt (e.g., Read, Write,etc.), and the like. In various embodiments, although many otherarrangements are possible, for purposes of illustration, a lowtransaction (L) may comprise a transaction having a value under a firstamount (e.g., $100), while a medium transaction (M) may comprise atransaction having a value between the first amount and a second amount(e.g., $100 and $500), and a high transaction (H) may comprise atransaction having a value greater than the second amount (e.g., $500).

Thus, table 1602 may be organized by entity, collection, level, and/ortime period, and each coefficient or element in table 1602 maycorrespond to a count or tally associated with each entity in acollection at a particular level. For instance, where level datacomprises a transaction amount or value, such as L, M, or H, asdepicted, each element in table 1602 may comprise a number oftransactions of one of these types by a particular customer collectionwith a particular merchant entity during a given time period. In variousembodiments, and as shown, system 1500 may limit an element to a valueof one or zero (e.g., based upon the assumption that a customertypically only makes one purchase from a given merchant during a singletime period). However, in various embodiments, each element may simplyact as a counter which may be incremented each time the customer makes apurchase from the merchant of the particular level type during theparticular time period. An array dimension or element may be sized (or asize may be allocated for a particular element) based upon an expectedor maximum number of bits required. Thus, in various embodiments, astructure 1602 may losslessly store data, as described herein. Inaddition, a count may be converted to and stored as (e.g., as describedabove) a binary value, which may speed data analysis and processing.

Referring to FIG. 17, a table 1702, much akin to table 1602, is shown.Table 1702 may, like table 1602, aggregate a count associated with anentity in a collection by level. Likewise, table 1702 may aggregate sucha count for one or more time periods, e.g., one or more months, asshown. Thus, in various embodiments, table 1702 may aggregate one ormore monthly totals, such as monthly totals for a number of transactionsa customer has engaged in with a particular merchant at a particularlevel. In various embodiments, it may be advantageous (e.g., storagerequirements may again be reduced) to remove or delete from any tablesummarizing a time period (e.g., table 1702, which summarizes oraggregates a total number of counts for a particular month) any leveltotals for a collection which are zero across all of a set of entities.For example, with regard to table 1702, it may be advantageous to removethe medium (or M) level data for Cust2, since the customer is not shownto have a transaction with any merchant entity during the month. Invarious embodiments, level data may be removed, as described above, withthe assistance of a cross reference table formed between a summarytable, such as table 1702, and a deletion table, which may track whichrows (having zero values) have been removed from a table, such as table1702. Although such an approach may, in certain embodiments, reduce asize associated with a summary table, e.g., table 1702, it maynevertheless require the creation of cross reference and deletiontables, which may require additional time and resources. Thus, invarious embodiments, it may be advantageous to forgo the removal oflevel data from a summary table.

In various embodiments, the systems and methods discussed herein may beused for a large variety of purposes. For example, in variousembodiments, each of the systems and methods may assist in thedetermination of one or more post purchasing opportunities, such as oneor more offers (e.g., loyalty offers), one or more discounts on futurepurchases, one or more rewards points, and the like. Further, asdescribed variously above, transaction history data may be manipulatedand analyzed in real time and/or pseudo or near real time, such that acustomer is provided a post purchasing opportunity within a short timeafter completing a transaction with a merchant (e.g., seemingly almostinstantly, such as, within several seconds or minutes of a transaction).A customer may be provided a post purchasing opportunity, in variousembodiments, in association with a same merchant from which a purchasewas recently made, in association with a merchant partnered with amerchant from whom a sale was recently made (e.g., such that themerchant and partner merchant may offer cross-sales opportunities toboost sales between themselves), and/or in association with a merchantthat is frequently attended or visited by the customer (e.g., to rewardcustomer loyalty to the frequently attended merchant).

Further, in various embodiments, the systems and methods discussedherein may assist in the determination of one or more pre-purchasingopportunities. For example, a customer may indicate, prior to or duringa visit to a merchant (e.g., an online visit and/or a visit to a brickand mortar store), that the customer intends to visit or is visiting themerchant, whereupon the systems and methods described herein may be usedto provide an opportunity (e.g., a discount, an offer, etc.) to thecustomer.

Any of the opportunities described above may be provided, in variousembodiments, based upon the transaction history of the customer, whichmay be maintained, as described herein, in a data structure such as, forexample, any of the tables described above (including tables 1602 and ortable 1702). Tables may be analyzed by a system (e.g., system 1502) todetermine that a customer shopped at a particular merchant on a certainnumber of days during a month and/or that the customer shopped atmerchants within a particular industry group, and a (post purchasingand/or pre-purchasing opportunity) may be determined and/or offered tothe customer in accordance with the determination. For instance, whereit is determined that a customer shopped with a particular merchant(e.g., a low priced merchant), as discussed above, the customer may beprovided with an opportunity (e.g., a coupon or offer) associated withanother or the same merchant (e.g., the low priced merchant). Further,the customer may be provided with such an opportunity in real timeand/or near real time, because the systems and methods discussed hereinpermit the storage and manipulation of large quantities of data within arelatively short amount of time and based upon one or more logical orbitwise operations.

Systems, methods and computer program products are provided. In thedetailed description herein, references to “various embodiments”, “oneembodiment”, “an embodiment”, “an example embodiment”, etc., indicatethat the embodiment described may include a particular feature,structure, or characteristic, but every embodiment may not necessarilyinclude the particular feature, structure, or characteristic. Moreover,such phrases are not necessarily referring to the same embodiment.Further, when a particular feature, structure, or characteristic isdescribed in connection with an embodiment, it is submitted that it iswithin the knowledge of one skilled in the art to effect such feature,structure, or characteristic in connection with other embodimentswhether or not explicitly described. After reading the description, itwill be apparent to one skilled in the relevant art(s) how to implementthe disclosure in alternative embodiments.

Any communication, transmission and/or channel discussed herein mayinclude any system or method for delivering content (e.g. data,information, metadata, etc.), and/or the content itself. The content maybe presented in any form or medium, and in various embodiments, thecontent may be delivered electronically and/or capable of beingpresented electronically. For example, a channel may comprise a website,a uniform resource locator (“URL”), a document (e.g., a Microsoft Worddocument, a Microsoft Excel document, an Adobe .pdf document, etc.), an“ebook,” an “emagazine,” an application or microapplication (asdescribed below), an SMS or other type of text message, an email,facebook, twitter, MMS, data communication over a financial acquirernetwork, and/or other type of communication technology. In variousembodiments, a channel may be hosted or provided by a data partner.

In various embodiments, the methods described herein are implementedusing the various particular machines described herein. The methodsdescribed herein may be implemented using the below particular machines,and those hereinafter developed, in any suitable combination, as wouldbe appreciated immediately by one skilled in the art. Further, as isunambiguous from this disclosure, the methods described herein mayresult in various transformations of certain articles.

For the sake of brevity, conventional data networking, applicationdevelopment and other functional aspects of the systems (and componentsof the individual operating components of the systems) may not bedescribed in detail herein. Furthermore, the connecting lines shown inthe various figures contained herein are intended to represent exemplaryfunctional relationships and/or physical couplings between the variouselements. It should be noted that many alternative or additionalfunctional relationships or physical connections may be present in apractical system.

The various system components discussed herein may include one or moreof the following: a host server or other computing systems including aprocessor for processing digital data; a memory coupled to the processorfor storing digital data; an input digitizer coupled to the processorfor inputting digital data; an application program stored in the memoryand accessible by the processor for directing processing of digital databy the processor; a display device coupled to the processor and memoryfor displaying information derived from digital data processed by theprocessor; and a plurality of databases. Various databases used hereinmay include: user data, file system data, client data; merchant data;financial institution data; and/or like data useful in the operation ofthe system. As those skilled in the art will appreciate, user computermay include an operating system (e.g., Windows NT, Windows 95/98/2000,Windows XP, Windows Vista, Windows 7, OS2, UNIX, Linux, Solaris, MacOS,etc.) as well as various conventional support software and driverstypically associated with computers.

In various embodiments, the server may include application servers (e.g.WEB SPHERE, WEB LOGIC, MOSS). In various embodiments, the server mayinclude web servers (e.g. APACHE, IIS, GWS, SUN JAVA SYSTEM WEB SERVER).

As used herein, “transmit” may include sending electronic data from onesystem component to another over a network connection, Additionally, asused herein, “data” may include encompassing information such ascommands, queries, files, data for storage, and the like in digital orany other form.

As used herein, “issue a debit”, “debit” or “debiting” refers to eithercausing the debiting of a stored value or prepaid card-type financialaccount, or causing the charging of a credit or charge card-typefinancial account, as applicable.

Phrases and terms similar to an “item” may include any good, service,information, experience, data, content, access, rental, lease,contribution, account, credit, debit, benefit, right, reward, points,coupons, credits, monetary equivalent, anything of value, something ofminimal or no value, monetary value, non-monetary value and/or the like.

The system contemplates uses in association with web services, utilitycomputing, pervasive and individualized computing, security and identitysolutions, autonomic computing, cloud computing, commodity computing,mobility and wireless solutions, open source, biometrics, grid computingand/or mesh computing.

Any databases discussed herein may include relational, hierarchical,graphical, or object-oriented structure and/or any other databaseconfigurations. Common database products that may be used to implementthe databases include DB2 by IBM (Armonk, N.Y.), various databaseproducts available from Oracle Corporation (e.g., MySQL) (RedwoodShores, Calif.), Microsoft Access or Microsoft SQL Server by MicrosoftCorporation (Redmond, Wash.), or any other suitable database product.Moreover, the databases may be organized in any suitable manner, forexample, as data tables or lookup tables. Each record may be a singlefile, a series of files, a linked series of data fields or any otherdata structure. Association of certain data may be accomplished throughany desired data association technique such as those known or practicedin the art. For example, the association may be accomplished eithermanually or automatically. Automatic association techniques may include,for example, a database search, a database merge, GREP, AGREP, SQL,using a key field in the tables to speed searches, sequential searchesthrough all the tables and files, sorting records in the file accordingto a known order to simplify lookup, and/or the like. The associationstep may be accomplished by a database merge function, for example,using a “key field” in pre-selected databases or data sectors, Variousdatabase tuning steps are contemplated to optimize database performance.For example, frequently used files such as indexes may be placed onseparate file systems to reduce In/Out (“I/O”) bottlenecks.

More particularly, a “key field” partitions the database according tothe high-level class of objects defined by the key field. For example,certain types of data may be designated as a key field in a plurality ofrelated data tables and the data tables may then be linked on the basisof the type of data in the key field. The data corresponding to the keyfield in each of the linked data tables is preferably the same or of thesame type. However, data tables having similar, though not identical,data in the key fields may also be linked by using AGREP, for example.In accordance with one embodiment, any suitable data storage techniquemay be utilized to store data without a standard format. Data sets maybe stored using any suitable technique, including, for example, storingindividual files using an ISO/IEC 7816-4 file structure; implementing adomain whereby a dedicated file is selected that exposes one or moreelementary files containing one or more data sets; using data setsstored in individual files using a hierarchical filing system; data setsstored as records in a single file (including compression, SQLaccessible, hashed via one or more keys, numeric, alphabetical by firsttuple, etc.); Binary Large Object (BLOB); stored as ungrouped dataelements encoded using ISO/IEC 7816-6 data elements; stored as ungroupeddata elements encoded using ISO/IEC Abstract Syntax Notation (ASN.1) asin ISO/IEC 8824 and 8825; and/or other proprietary techniques that mayinclude fractal compression methods, image compression methods, etc.

In one exemplary embodiment, the ability to store a wide variety ofinformation in different formats is facilitated by storing theinformation as a BLOB. Thus, any binary information can be stored in astorage space associated with a data set. As discussed above, the binaryinformation may be stored on the financial transaction instrument orexternal to but affiliated with the financial transaction instrument.The BLOB method may store data sets as ungrouped data elements formattedas a block of binary via a fixed memory offset using either fixedstorage allocation, circular queue techniques, or best practices withrespect to memory management (e.g., paged memory, least recently used,etc.). By using BLOB methods, the ability to store various data setsthat have different formats facilitates the storage of data associatedwith the financial transaction instrument by multiple and unrelatedowners of the data sets. For example, a first data Set which may bestored may be provided by a first party, a second data set which may bestored may be provided by an unrelated second party, and yet a thirddata set which may be stored, may be provided by an third partyunrelated to the first and second party. Each of these three exemplarydata sets may contain different information that is stored usingdifferent data storage formats and/or techniques. Further, each data setmay contain subsets of data that also may be distinct from othersubsets.

As stated above, in various embodiments, the data can be stored withoutregard to a common format. However, in one exemplary embodiment, thedata set (e.g., BLOB) may be annotated in a standard manner whenprovided for manipulating the data onto the financial transactioninstrument. The annotation may comprise a short header, trailer, orother appropriate indicator related to each data set that is configuredto convey information useful in managing the various data sets. Forexample, the annotation may be called a “condition header”, “header”,“trailer”, or “status”, herein, and may comprise an indication of thestatus of the data set or may include an identifier correlated to aspecific issuer or owner of the data. In one example, the first threebytes of each data set BLOB may be configured or configurable toindicate the status of that particular data set; e.g., LOADED,INITIALLIZED, READY, BLOCKED, REMOVABLE, or DELETED. Subsequent bytes ofdata may be used to indicate for example, the identity of the issuer,user, transaction/membership account identifier or the like. Each ofthese condition annotations are further discussed herein.

The data set annotation may also be used for other types of statusinformation as well as various other purposes. For example, the data setannotation may include security information establishing access levels.The access levels may, for example, be configured to permit or monitoronly certain individuals, levels of employees, companies, or otherentities accessing data sets, or to permit or monitor access to specificdata sets based on the transaction, merchant, issuer, user or the like.Furthermore, the security information may restrict, permit, and/ormonitor only certain actions such as accessing, modifying, and/ordeleting data sets. In one example, the data set annotation may indicateor track that only the data set owner or the user are permitted todelete a data set, various identified users may be permitted to accessthe data set for reading, and others are altogether excluded fromaccessing the data set. However, other access restriction or monitoringmay also be used Which may allow various entities to access a data setwith various permission levels as appropriate, and/or which monitoringmay also be used to track various entities (e.g., users or systems)accessing a data set with various permission levels. Thus, in variousembodiments, tracking information may enable a system administrator toinquire into one or more user activities, which inquiry may permit thesystem administrator to adjust one or more access controls, modify oneor more user groups or transaction clusters, and the like.

The data, including the header or trailer may be received by a standalone interaction device configured to add, delete, modify, or augmentthe data in accordance with the header or trailer. As such, in oneembodiment, the header or trailer is not stored on the transactiondevice along with the associated issuer-owned data but instead theappropriate action may be taken by providing to the transactioninstrument user at the stand alone device, the appropriate option forthe action to be taken. The system may contemplate a data storagearrangement wherein the header or trailer, or header or trailer history,of the data is stored on the transaction instrument in relation to theappropriate data.

One skilled in the art will also appreciate that, for security reasons,any databases, systems, devices, servers or other components of thesystem may consist of any combination thereof at a single location or atmultiple locations, wherein each database or system includes any ofvarious suitable security features, such as firewalls, access codes,encryption, decryption, compression, decompression, and/or the like.

Encryption may be performed by way of any of the techniques nowavailable in the art or which may become available—e.g., AES, Twofish,RSA, El Gamal, Schorr signature, DSA, PGP, PKI, GPG (GnuPG) ECC, andsymmetric and asymmetric cryptosystems.

The computing unit of the web client may be further equipped with anInternet browser connected to the Internet or an intranet using standarddial-up, cable, DSL or any other Internet protocol known in the art.Transactions originating at a web client may pass through a firewall inorder to prevent unauthorized access from users of other networks.Further, additional firewalls may be deployed between the varyingcomponents of CMS to further enhance security.

Firewall may include any hardware and/or software suitably configured toprotect CMS components and/or enterprise computing resources from usersof other networks. Further, a firewall may be configured to limit orrestrict access to various systems and components behind the firewallfor web clients connecting through a web server. Firewall may reside invarying configurations including Stateful Inspection, Proxy based,access control lists, and Packet Filtering among others. Firewall may beintegrated within an web server or any other CMS components or mayfurther reside as a separate entity. A firewall may implement networkaddress translation (“NAT”) and/or network address port translation(“NAPT”). A firewall may accommodate various tunneling protocols tofacilitate secure communications, such as those used in virtual privatenetworking. A firewall may implement a demilitarized zone (“DMZ”) tofacilitate communications with a public network such as the Internet. Afirewall may be integrated as software within an Internet server, anyother application server components or may reside within anothercomputing device or may take the form of a standalone hardwarecomponent.

The computers discussed herein may provide a suitable website or otherInternet-based graphical user interface which is accessible by users. Inone embodiment, the Microsoft Internet Information Server (IIS),Microsoft Transaction Server (MTS), and Microsoft SQL Server, are usedin conjunction with the Microsoft operating system, Microsoft NT webserver software, a Microsoft SQL Server database system, and a MicrosoftCommerce Server. Additionally, components such as Access or MicrosoftSQL Server, Oracle, Sybase, Informix MySQL, Interbase, etc., may be usedto provide an Active Data Object (ADO) compliant database managementsystem. In one embodiment, the Apache web server is used in conjunctionwith a Linux operating system, a MySQL database, and the Perl, PHP,and/or Python programming languages.

Any of the communications, inputs, storage, databases or displaysdiscussed herein may be facilitated through a website having web pages.The term “web page” as it is used herein is not meant to limit the typeof documents and applications that might be used to interact with theuser. For example, a typical website might include, in addition tostandard HTML documents, various forms, Java applets, JavaScript, activeserver pages (ASP), common gateway interface scripts (CGI), extensiblemarkup language (XML), dynamic HTML, cascading style sheets (CSS), AJAX(Asynchronous Javascript And XML), helper applications, plug-ins, andthe like. A server may include a web service that receives a requestfrom a web server, the request including a URL(http://yahoo.com/stockquotes/ge) and an IP address (123.56.789.234).The web server retrieves the appropriate web pages and sends the data orapplications for the web pages to the IP address. Web services areapplications that are capable of interacting with other applicationsover a communications means, such as the internet. Web services aretypically based on standards or protocols such as XML, SOAP, AJAX, WSDLand UDDI. Web services methods are well known in the art, and arecovered in many standard texts. See, e.g., Alex Aghiem, IT Web Services:A Roadmap for the Enterprise (2003), hereby incorporated by reference.

Middleware may include any hardware and/or software suitably configuredto facilitate communications and/or process transactions betweendisparate computing systems. Middleware components are commerciallyavailable and known in the art. Middleware may be implemented throughcommercially available hardware and/or software, through custom hardwareand/or software components, or through a combination thereof. Middlewaremay reside in a variety of configurations and may exist as a standalonesystem or may be a software component residing on the Internet server.Middleware may be configured to process transactions between the variouscomponents of an application server and any number of internal orexternal systems for any of the purposes disclosed herein. WebSphere MQ™(formerly MQSeries) by IBM, Inc. (Armonk, N.Y.) is an example of acommercially available middleware product. An Enterprise Service Bus(“ESB”) application is another example of middleware.

Practitioners will also appreciate that there are a number of methodsfor displaying data within a browser-based document. Data may berepresented as standard text or within a fixed list, scrollable list,drop-down list, editable text field, fixed text field, pop-up window,and the like. Likewise, there are a number of methods available formodifying data in a web page such as, for example, free text entry usinga keyboard, selection of menu items, check boxes, option boxes, and thelike.

The system and method may be described herein in terms of functionalblock components, screen shots, optional selections and variousprocessing steps. It should be appreciated that such functional blocksmay be realized by any number of hardware and/or software componentsconfigured to perform the specified functions. For example, the systemmay employ various integrated circuit components, e.g., memory elements,processing elements, logic elements, look-up tables, and the like, whichmay carry out a variety of functions under the control of one or moremicroprocessors or other control devices. Similarly, the softwareelements of the system may be implemented with any programming orscripting language such as C, C++, C#, Java, JavaScript, VBScript,Macromedia Cold Fusion, COBOL, Microsoft Active Server Pages, assembly,PERL, PHP, awk, Python, Visual Basic, SQL Stored Procedures, PL/SQL, anyUNIX shell script, and extensible markup language (XML) with the variousalgorithms being implemented with any combination of data structures,objects, processes, routines or other programming elements. Further, itshould be noted that the system may employ any number of conventionaltechniques for data transmission, signaling, data processing, networkcontrol, and the like. Still further, the system could be used to detector prevent security issues with a client-side scripting language, suchas JavaScript, VBScript or the like. For a basic introduction ofcryptography and network security, see any of the following references:(1) “Applied Cryptography: Protocols, Algorithms, And Source Code In C,”by Bruce Schneier, published by John Wiley & Sons (second edition,1995); (2) “Java Cryptography” by Jonathan Knudson, published byO'Reilly & Associates (1998); (3) “Cryptography & Network Security:Principles & Practice” by William Stallings, published by Prentice Hall;all of which are hereby incorporated by reference.

Each participant is equipped with a computing device in order tointeract with the system and facilitate online commerce transactions.The customer has a computing unit in the form of a personal computer,although other types of computing units may be used including laptops,notebooks, hand held computers, set-top boxes, cellular or mobiletelephones, touch-tone telephones and the like. The merchant has acomputing unit implemented in the form of a computer-server, althoughother implementations are contemplated by the system. The bank has acomputing center shown as a main frame computer. However, the bankcomputing center may be implemented in other forms, such as amini-computer, a PC server, a network of computers located in the sameof different geographic locations, or the like. Moreover, the systemcontemplates the use, sale or distribution of any goods, services orinformation over any network having similar functionality describedherein

The merchant computer and the bank computer may be interconnected via asecond network, referred to as a payment network. The payment networkwhich may be part of certain transactions represents existingproprietary networks that presently accommodate transactions for creditcards, debit cards, and other types of financial/banking cards. Thepayment network is a closed network that is assumed to be secure fromeavesdroppers. Exemplary transaction networks may include the AMERICANEXPRESS, VISANET and the VERIPHONE networks.

The electronic commerce system may be implemented at the customer andissuing bank. In an exemplary implementation, the electronic commercesystem is implemented as computer software modules loaded onto thecustomer computer and the banking computing center. The merchantcomputer does not require any additional software to participate in theonline commerce transactions supported by the online commerce system.

As will be appreciated by one of ordinary skill in the art, the systemmay be embodied as a customization of an existing system, an add-onproduct, a processing apparatus executing upgraded software, a standalone system, a distributed system, a method, a data processing system,a device for data processing, and/or a computer program product.Accordingly, any portion of the system or a module may take the form ofa processing apparatus executing code, an interne based embodiment, anentirely hardware embodiment, or an embodiment combining aspects of theinternet, software and hardware. Furthermore, the system may take theform of a computer program product on a computer-readable storage mediumhaving computer-readable program code means embodied in the storagemedium. Any suitable computer-readable storage medium may be utilized,including hard disks, CD-ROM, optical storage devices, magnetic storagedevices, and/or the like.

The system and method is described herein with reference to screenshots, block diagrams and flowchart illustrations of methods, apparatus(e.g., systems), and computer program products according to variousembodiments. It will be understood that each functional block of theblock diagrams and the flowchart illustrations, and combinations offunctional blocks in the block diagrams and flowchart illustrations,respectively, can be implemented by computer program instructions.

These computer program instructions may be loaded onto a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructionsthat execute on the computer or other programmable data processingapparatus create means for implementing the functions specified in theflowchart block or blocks. These computer program instructions may alsobe stored in a computer-readable memory that can direct a computer orother programmable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including instruction meanswhich implement the function specified in the flowchart block or blocks.The computer program instructions may also be loaded onto a computer orother programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmableapparatus to produce a computer-implemented process such that theinstructions which execute on the computer or other programmableapparatus provide steps for implementing the functions specified in theflowchart block or blocks.

Accordingly, functional blocks of the block diagrams and flowchartillustrations support combinations of means for performing the specifiedfunctions, combinations of steps for performing the specified functions,and program instruction means for performing the specified functions. Itwill also be understood that each functional block of the Hock diagramsand flowchart illustrations, and combinations of functional blocks inthe block diagrams and flowchart illustrations, can be implemented byeither special purpose hardware-based computer systems which perform thespecified functions or steps, or suitable combinations of specialpurpose hardware and computer instructions. Further, illustrations ofthe process flows and the descriptions thereof may make reference touser windows, webpages, websites, web forms, prompts, etc. Practitionerswill appreciate that the illustrated steps described herein may comprisein any number of configurations including the use of windows, webpages,web forms, popup windows, prompts and the like. It should be furtherappreciated that the multiple steps as illustrated and described may becombined into single webpages and/or windows but have been expanded forthe sake of simplicity. In other cases, steps illustrated and describedas single process steps may be separated into multiple webpages and/orwindows but have been combined for simplicity.

The term “non-transitory” is to be understood to remove only propagatingtransitory signals per se from the claim scope and does not relinquishrights to all standard computer-readable media that are not onlypropagating transitory signals per se. Stated another way, the meaningof the term “non-transitory computer-readable medium” and“non-transitory computer-readable storage medium” should be construed toexclude only those types of transitory computer-readable media whichwere found in In Re Nuijten to fall outside the scope of patentablesubject matter under 35 U.S.C. §101.

Benefits, other advantages, and solutions to problems have beendescribed herein with regard to specific embodiments. However, thebenefits, advantages, solutions to problems, and any elements that maycause any benefit, advantage, or solution to occur or become morepronounced are not to be construed as critical, required, or essentialfeatures or elements of the disclosure. The scope of the disclosure isaccordingly to be limited by nothing other than the appended claims, inwhich reference to an element in the singular is not intended to mean“one and only one” unless explicitly so stated, but rather “one ormore.” Moreover, where a phrase similar to ‘at least one of A, B, and C’or ‘at least one of A, B, or C’ is used in the claims or specification,it is intended that the phrase be interpreted to mean that A alone maybe present in an embodiment, B alone may be present in an embodiment, Calone may be present in an embodiment, or that any combination of theelements A, B and C may be present in a single embodiment; for example,A and B, A and C. B and C, or A and B and C. Although the disclosureincludes a method, it is contemplated that it may be embodied ascomputer program instructions on a tangible computer-readable carrier,such as a magnetic or optical memory or a magnetic or optical disk. Allstructural, chemical, and functional equivalents to the elements of theabove-described exemplary embodiments that are known to those ofordinary skill in the art are expressly incorporated herein by referenceand are intended to be encompassed by the present claims. Moreover, itis not necessary for a device or method to address each and everyproblem sought to be solved by the present disclosure, for it to beencompassed by the present claims. Furthermore, no element, component,or method step in the present disclosure is intended to be dedicated tothe public regardless of whether the element, component, or method stepis explicitly recited in the claims. No claim element herein is to beconstrued under the provisions of 35 U.S.C. 112, sixth paragraph, unlessthe element is expressly recited using the phrase “means for.” As usedherein, the terms “comprises”, “comprising”, or any other variationthereof, are intended to cover a non-exclusive inclusion, such that aprocess, method, article, or apparatus that comprises a list of elementsdoes not include only those elements but may include other elements notexpressly listed or inherent to such process, method, article, orapparatus.

Phrases and terms similar to “account”, “account number”, “account code”or “consumer account” as used herein, may include any device, code(e.g., one or more of an authorization/access code, personalidentification number (“PIN”), Internet code, other identification code,and/or the like), number, letter, symbol, digital certificate, smartchip, digital signal, analog signal, biometric or otheridentifier/indicia suitably configured to allow the consumer to access,interact with or communicate with the system. The account number mayoptionally be located on or associated with a rewards account, chargeaccount, credit account, debit account, prepaid account, telephone card,embossed card, smart card, magnetic stripe card, bar code card,transponder, radio frequency card or an associated account.

The system may include or interface with any of the foregoing accounts,devices, and/or a transponder and reader (e.g. RFID reader) in RFcommunication with the transponder (which may include a fob), orcommunications between an initiator and a target enabled by near fieldcommunications (NFC). Typical devices may include, for example, a keyring, tag, card, cell or mobile phone, wristwatch or any such formcapable of being presented for interrogation. Moreover, the system,computing unit or device discussed herein may include a “pervasivecomputing device,” which may include a traditionally non-computerizeddevice that is embedded with a computing unit. Examples may includewatches, Internet enabled kitchen appliances, restaurant tables embeddedwith RF readers, wallets or purses with imbedded transponders, etc.Furthermore, a device or financial transaction instrument may haveelectronic and communications functionality enabled, for example, by: anetwork of electronic circuitry that is printed or otherwiseincorporated onto or within the transaction instrument (and typicallyreferred to as a “smart card”); a fob having a transponder and an REDreader; and/or near field communication (NFC) technologies. For moreinformation regarding NFC, refer to the following specifications all ofwhich are incorporated by reference herein; ISO/IEC 18092/ECMA-340, ISO14443, Near Field Communication Interface and Protocol-1 (NFCIP-1);ISO/IEC 21481/ECMA-352, Near Field Communication interface andProtocol-2 (NFCIP-2); and EMV 4.2 available athttp://www.envco.com/default.aspx.

The account number may be distributed and stored in any form of plastic,electronic, magnetic, radio frequency, wireless, audio and/or opticaldevice capable of transmitting or downloading data from itself to asecond device. A consumer account number may be, for example, asixteen-digit account number, although each credit provider has its ownnumbering system, such as the fifteen-digit numbering system used byAmerican Express. Each company's account numbers comply with thatcompany's standardized format such that the company using afifteen-digit format will generally use three-spaced sets of numbers, asrepresented by the number “0000 000000 00000”. The first five to sevendigits are reserved for processing purposes and identify the issuingbank, account type, etc. In this example, the last (fifteenth) digit isused as a sum check for the fifteen digit number. The intermediaryeight-to-eleven digits are used to uniquely identify the consumer. Amerchant account number may be, for example, any number or alpha-numericcharacters that identify a particular merchant for purposes of accountacceptance, account reconciliation, reporting, or the like.

In various embodiments, an account number may identify a consumer. Inaddition, in various embodiments, a consumer may be identified by avariety of identifiers, including, for example, an email address, atelephone number, a cookie id, a radio frequency identifier (RFID), abiometric, and the like.

The terms “payment vehicle,” “financial transaction instrument,”“transaction instrument” and/or the plural form of these terms may beused interchangeably throughout to refer to a financial instrument.

Phrases and terms similar to “merchant,” “supplier” or “seller” mayinclude any entity that receives payment or other consideration. Forexample, a supplier may request payment for goods sold to a buyer whoholds an account with a transaction account issuer.

Phrases and terms similar to “internal data” may include any data acredit issuer possesses or acquires pertaining to a particular consumer.Internal data may be gathered before, during, or after a relationshipbetween the credit issuer and the transaction account holder (e.g., theconsumer or buyer). Such data may include consumer demographic data.Consumer demographic data includes any data pertaining to a consumer.Consumer demographic data may include, for example, consumer name,address, telephone number, email address, employer and social securitynumber. Consumer transactional data is any data pertaining to theparticular transactions in which a consumer engages during any giventime period. Consumer transactional data may include, for example,transaction amount, transaction time, transaction vendor/merchant, andtransaction vendor/merchant location. Transaction vendor/merchantlocation may contain a high degree of specificity to a vendor/merchant.For example, transaction vendor/merchant location may include aparticular gasoline filing station in a particular postal code locatedat a particular cross section or address. Also, for example, transactionvendor/merchant location may include a particular web address, such as aUniform Resource Locator (“URL”), an email address and/or an InternetProtocol (“IP”) address for a vendor/merchant. Transactionvendor/merchant, and transaction vendor/merchant, location may beassociated with a particular consumer and further associated with setsof consumers. Consumer payment data includes any data pertaining to aconsumer's history of paying debt obligations. Consumer payment data mayinclude consumer payment dates, payment amounts, balance amount, andcredit limit. Internal data may further comprise records of consumerservice calls, complaints, requests for credit line increases,questions, and comments. A record of a consumer service call includes,for example, date of call, reason for call, and any transcript orsummary of the actual call.

Phrases similar to a “payment processor” may include a company (e.g., athird party) appointed (e.g., by a merchant) to handle transactions. Apayment processor may include an issuer, acquirer, authorizer and/or anyother system or entity involved in the transaction process. Paymentprocessors may be broken down into two types: front-end and back-end.Front-end payment processors have connections to various transactionaccounts and supply authorization and settlement services to themerchant banks' merchants. Back-end payment processors acceptsettlements from front-end payment processors and, via The FederalReserve Bank, move money from an issuing bank to the merchant hank. Inan operation that will usually take a few seconds, the payment processorwill both check the details received by forwarding the details to therespective account's issuing bank or card association for verification,and may carry out a series of anti-fraud measures against thetransaction. Additional parameters, including the account's country ofissue and its previous payment history, may be used to gauge theprobability of the transaction being approved. In response to thepayment processor receiving confirmation that the transaction accountdetails have been verified, the information may be relayed back to themerchant, who will then complete the payment transaction. In response tothe verification being denied, the payment processor relays theinformation to the merchant, who may then decline the transaction.Phrases similar to a “payment gateway” or “gateway” may include anapplication service provider service that authorizes payments fore-businesses, online retailers, and/or traditional brick and mortarmerchants. The gateway may be the equivalent of a physical point of saleterminal located in most retail outlets. A payment gateway may protecttransaction account details by encrypting sensitive information, such astransaction account numbers, to ensure that information passes securelybetween the customer and the merchant and also between merchant andpayment processor.

What is claimed is:
 1. A method, comprising: receiving, by a computingsystem, access information for a first file of a plurality of filesstored in a data repository, wherein the access information indicates atype of one or more file access attempts to the first file by a first ofa plurality of users; storing, by the computer system in an access arrayelement of a file access data array corresponding to the first user andthe first file, file access information indicative of the one or morefile access attempts of the first file, wherein the access array elementalso includes file access information indicative of other file accessattempts to other files of the plurality of files; determining, with thecomputing system based on the file access data array, a first risk levelof the first user's one or more access attempts of the first file; andstoring, by the computer system in a risk array element of a risk levelarray corresponding to the first user and the first file, risk levelinformation indicative of the first risk level, wherein the risk arrayelement also includes risk level information indicative of other risklevels corresponding to access attempts to other files of the pluralityof files by the first user.
 2. The method of claim 1, wherein the typeof one or more file access attempts indicates at least whether a givenaccess attempt included read or write operations.
 3. The method of claim1, wherein the other files of the plurality of files in the datarepository are assigned unique powers of two, wherein the respectivefile access information indicative of respective other file accessattempts to the other files is stored in respective position of theaccess array element based on the unique power of two assigned to therespective other file.
 4. The method of claim 1, further comprising:adjusting one or more access controls for the data repository and one ormore users based on one or more of the risk levels.
 5. The method ofclaim 1, further comprising: identifying, based on the file access dataarray, one or more files that the first user was authorized to accessbut did not access.
 6. The method of claim 1, wherein the risk levelsare further determined based on potential impact of harmful accesses,wherein the potential impact is determined based on the accessinformation.
 7. The method of claim 1, wherein the access informationfor the first file includes a maximum access type attempted.
 8. Themethod of claim 1, wherein the access information includes a number ofaccesses made by the first user to the first file.
 9. A non-transitorycomputer-readable medium having instructions stored thereon that areexecutable by a computing device to perform operations comprising:receiving access information for a first file of a plurality of filesstored in a data repository, wherein the access information indicates atype of one or more file access attempts to the first file by a first ofa plurality of users; storing, in an access array element of a fileaccess data array corresponding to the first user and the first file,file access information indicative of the one or more file accessattempts of the first file, wherein the access array element alsoincludes file access information indicative of other file accessattempts to other files of the plurality of files; determining, based onthe file access data array, a first risk level of the first user's oneor more access attempts of the first file; and storing, in a risk arrayelement of a risk level array corresponding to the first user and thefirst file, risk level information indicative of the first risk level,wherein the risk array element also includes risk level informationindicative of other risk levels corresponding to access attempts toother files of the plurality of files by the first user.
 10. Thenon-transitory computer-readable medium of claim 9, wherein the risklevel is associated with at least one of likelihood of harmful accessesor impact of harmful accesses.
 11. The non-transitory computer-readablemedium of claim 9, wherein the type of one or more file access attemptscomprises one or more of: read, write, or delete.
 12. The non-transitorycomputer-readable medium of claim 9, wherein the access informationincludes one or more file access results corresponding to the one ormore file access attempts, wherein the file access results include oneor more of: granted or denied.
 13. The non-transitory computer-readablemedium of claim 9, wherein the access information includes a number ofaccesses made by the first user to the first file.
 14. Thenon-transitory computer-readable medium of claim 9, wherein theoperations further comprise: adjusting one or more authorizations forthe data repository and one or more users based on one or more of thestored risk levels.
 15. The non-transitory computer-readable medium ofclaim 9, wherein the access information includes a maximum number of aparticular access type.
 16. The non-transitory computer-readable mediumof claim 9, wherein the operations further comprise: determining, basedon the access information, excessive granted access.
 17. Thenon-transitory computer-readable medium of claim 9, wherein theoperations further comprise: determining, based on the accessinformation, potential malicious attempted access.
 18. A system,comprising: one or more processors; and one or more memories havingprogram instructions stored thereon that are executable by the one ormore processors to cause the system to perform operations comprising:receiving access information for a first file of a plurality of filesstored in a data repository, wherein the access information indicates atype of one or more file access attempts to the first file by a first ofa plurality of users; storing, in an access array element of a fileaccess data array corresponding to the first user and the first file,file access information indicative of the one or more file accessattempts of the first file, wherein the access array element alsoincludes file access information indicative of other file accessattempts to other files of the plurality of files; determining, based onthe file access data array, a first risk level of the first user's oneor more access attempts of the first file; and storing, in a risk arrayelement of a risk level array corresponding to the first user and thefirst file, risk level information indicative of the first risk level,wherein the risk array element also includes risk level informationindicative of other risk levels corresponding to access attempts toother files of the plurality of files by the first user.
 19. The systemof claim 18, wherein the operations further comprise: determiningwhether a user in the plurality of users accessed the data repository.20. The system of claim 18, wherein the access information indicates atleast whether a given access attempt included read or modify operationsand whether the given access attempt was granted based on one or moresecurity restrictions.